Profile and predictors of service needs for families of children with autism spectrum disorders

• Published in: Autism : the international journal of research and practice 2015-08, Vol.19 (6), p.673-683
• Main Authors: Hodgetts, Sandra, Zwaigenbaum, Lonnie, Nicholas, David
• Format: Article
• Language: English
• Subjects: Adolescent; Alberta (Edmonton); Autism; Autism Spectrum Disorder - rehabilitation; Autistic children; Canada; Child; Child Health Services; Child, Preschool; Children; Delivery Systems; Family; Family centered care; Family Needs; Family Needs Survey; Family support; Female; Foreign Countries; Health Services Accessibility; Health Services Needs and Demand; Humans; Linear analysis; Low income groups; Male; Mothers; Needs Assessment; Older children; Original; Parent Attitudes; Parents; Pervasive Developmental Disorders; Policy making; Polls & surveys; Predictor Variables; Qualitative Research; Quality of life; Regression (Statistics); Respite Care; Social Services; Social Support Groups; Socioeconomic Factors; Statistical Analysis; Surveys and Questionnaires
• ISSN: 1362-3613; 1461-7005
• DOI: 10.1177/1362361314543531

Purpose: Increasing demand for autism services is straining service systems. Tailoring services to best meet families’ needs could improve their quality of life and decrease burden on the system. We explored overall, best, and worst met service needs, and predictors of those needs, for families of children with autism spectrum disorders. Methods: Parents of 143 children with autism spectrum disorders (2–18 years) completed a survey including demographic and descriptive information, the Family Needs Survey–Revised, and an open-ended question about service needs. Descriptive statistics characterize the sample and determine the degree to which items were identified and met as needs. Predictors of total and unmet needs were modeled with regression or generalized linear model. Qualitative responses were thematically analyzed. Results: The most frequently identified overall and unmet service needs were information on services, family support, and respite care. The funding and quality of professional support available were viewed positively. Decreased child’s age and income and being an older mother predicted more total needs. Having an older child or mother, lower income, and disruptive behaviors predicted more total unmet needs, yet only disruptive behaviors predicted proportional unmet need. Child’s language or intellectual abilities did not predict needs. Conclusion: Findings can help professionals, funders, and policy-makers tailor services to best meet families’ needs.